Introduction
Protected Natural Areas (PNA) are sites that preserve environments representative of various biogeographical and ecological regions; their creation is a central part of conservation policies worldwide (Durand & Jimenez, 2010; Pabon-Zamora et al. 2008). PNAs are present in more than 169 countries and cover 15 % of the Earth's surface (International Union for Conservation of Nature [IUCN], 2016).
Currently, Mexico has 182 federal PNA, making up 90 839.52 km2 (Comisión Nacional de Áreas Naturales Protegidas [CONANP], 2019). The PNA have several management categories, amongst which National Parks stand out for their biodiversity and scenic beauty, which are associated with tourism and recreation. For the most part, PNAs are located on socially owned land, where 93 % of the population faces some degree of marginalization (Comisión Nacional para el Conocimiento y Uso de la Biodiversidad [CONABIO] 2009) and exerts continuous pressure on natural resources. In this regard, CONANP carries out conservation work and generates development alternatives for the populations that inhabit these areas, in order to mitigate the adverse effects on the environment and associated environmental services. However, the implementation of conservation policies in PNA depends directly on the personnel assigned and the availability of economic resources, which must be optimized to ensure efficient management and compliance with conservation objectives. Unfortunately, in Mexico there are PNA’s that still lack enough resources, field personnel or operating program for the management of the ecosystem that guarantees preservation.
Los Mármoles National Park (PNLM) has faced years of abandonment in management for conservation. In addition, productive activities incompatible with the management category (rain-fed agriculture, fruit farming, extensive and backyard livestock, extraction of natural resources and non-metallic minerals) were established and caused degradation of natural resources, habitat fragmentation, erosive processes and loss of soil productivity. This situation reflects the lack of economic development policies and budget allocation to carry out administrative, operational and monitoring actions (Consejo Nacional de Evaluación de la Política de Desarrollo Social [CONEVAL], 2016), both in the PNLM and in other PNA in Mexico.
Given the ecotouristic potential of the PNLM and the lack of job opportunities, the residents of La Encarnación, Municipality of Zimapan, Hidalgo, promoted a tourism development project in 2013. The Comisión Nacional Para el Desarrollo de los Pueblos Indígenas supported and funded this project through to the installation, equipment and training for the services of zip lining, rappelling, mountain biking, spelunking and hiking; however, the tourism that goes currently to the park (access charge free) demands for complementary services such as accommodation, transport, food, and access roads in good conditions, which must be valued by the community group in the planning of services that are intended to provide.
Disorderly tourism represents a source of environmental impacts (Quintero, 2004). In this sense, in the PNLM, tourism activity has taken place without planning that promotes the sustainable use of resources and optimizes Community Development. This is attributed to the lack of coordination between the area's residents and the park's administrative staff, as well as studies involving tourists ' preferences for landscape conservation. Therefore, in order to know the social preferences for the implementation of the improvement plan in four areas of intervention, the choice experiment method was applied. This tool provides information on the economic value of non-transactional environmental services in the market (Carson & Czajkowski, 2014; Hensher, Rose, & Greene, 2005); it also allows the decomposition of the total value of the environmental good in the value of its attributes, providing a more useful approach to economic valuation in an environmental management and policy perspective (Riera & Mogas, 2006).
The method of choice experiments was applied in market research since the 60s, and from the 80s in geography, tourism, transport, valuation of environmental goods, health economics, among others (Bekker-Grob, 2010; Brouwer et al., 2016; Cerda, 2011; Rocamora, Colombo, & Glenk, 2014; Tudela-Mamani & Leos-Rodriguez, 2018). With respect to the use of the method in the environmental goods valuation, Riera and Mogas (2006) estimated the impacts on social welfare due to the increase of the forest surface in Catalonia; Tudela (2010) assessed the social preferences for the management of the PNA in Mexico; and Cerda (2011) estimated the economic value of environmental services provided by forest ecosystems in Navarino island, Chile.
The objective of this work was to estimate the economic value of the implementation of the improvement plan (access roads, forest health, biodiversity protection and recreation spaces) for the management of Los Mármoles National Park, through choice experiments. This information will facilitate the decision-making of those responsible for the administration and promoters of community ecotourism.
Materials and methods
The investigation was carried out in the town of La Encarnación in Los Mármoles National Park. The PNLM is located in the northwest of the state of Hidalgo (20° 45’ 39” and 20° 58’ 22” LN and 99° 08’ 57 and 99° 18’ 39” LO), has a surface of 23 150 ha and occupies part of the municipalities of Jacala, Nicolás Flores, Pacula and Zimapán (Ramírez-Cruz, Sanchez-Gonzalez, & Tejero-Díez, 2009). The area belongs to the Priority Land region 101 Sierra Gorda-Rio Moctezuma, which is relevant in terms of diversity of flora and fauna, presents endemic species in some risk category (Randell-Badillo, 2008). This biological wealth translates into environmental goods and services for the population of the park and its area of influence, as well as landscape value that represents potential for the development of rural and ecological tourism.
Choice experiments method
The choice experiments method has its theoretical basis in the consumer choice model. According to Tudela-Mamani and Leos-Rodriguez (2018), Lancaster (1966) breaks with the traditional theory of consumer behavior by assuming that this demand goods by virtue of their characteristics, which generate utility. On the other hand, the theory of random utility assumes that a perfectly rational individual chooses the alternative that implies greater utility. In this sense, the method consisted of presenting sets of attribute options at different levels to the interviewees, who had to choose the preferred alternative j = 1, 2, ... J of the choice set C, consisting of a constant or status quo option (current situation) and two improvement plans. The interviewees' choice reflected their preference for the attributes of one alternative compared to the other two; that is, they assessed the changes in the attributes of their preference, which allowed them to transform their responses to estimates into monetary magnitudes.
The utility of the respondents, given their choices, is represented by the expression:
The probability that an individual chooses alternative m over any option
j in the choice set C is expressed as the
probability that the utility of the former is greater than that of the rest;
that is: P [
The indirect utility function (V) is expressed as a linear model of the parameters as follows:
where,
α |
specific constant for each alternative |
β |
vector of utility coefficients associated with the Z vector of explanatory variables |
γ |
coefficient associated with the price of alternative j, rate j |
δ |
vector of coefficients associated with socioeconomic variables (Blamey et al. 1999) |
The average effect of an attribute is the one it has on the V ij response variable and is independent of the effects of the other attributes.
Under the assumption that the error terms are independent and identically distributed with Gumbel or extreme value type I, the probability of choosing the alternative m is expressed with a multinomial logit (LMN) that contains the attributes to be evaluated and the characteristics of individuals (McFadden, 1974). In this model, ω represents the non-estimable scale parameter regardless of the function parameters (Alvarez-Farizo, Gil, & Howard, 2005):
P [
The estimated parameters of the additive model can be interpreted as marginal effects of the attribute of the asset to be valued on the probability of choosing one of the plans; in this sense, the marginal willingness to pay (DAPMg) is the willingness to pay for a unit change in each of the intervention areas, while the rest remains constant. The willingness to pay for a marginal change in any of the attributes analysed results from dividing the estimated coefficient of each attribute (-ßi) by the coefficient of the attribute rate (γ) (Alpizar, Carlsson, & Martinsson, 2001).
Procedure of the choice experiment
Prior to the application of the choice experiment a diagnosis of the environmental situation and the management of the PNA was necessary. To this end, meetings were held and interviews were applied to the staff responsible for the administration of the park and local authorities; in addition, a participatory diagnostic workshop was held with residents and tourist service prividers to identify the most relevant aspects of recreational activity. The problems encountered were as follows:
Impact on biodiversity. The vegetation cover has effects due to anthropogenic activities incompatible with the natural vocation and fragmentation of habitats; also, in recent years the hunting of felines has been recorded as a result of the attacks of these predators on livestock.
Increase in the incidence of pests, fire risk due to fuel accumulation and the presence of anthropogenic activities of local users and tourists.
Increased tourism demand for complementary services (v. g. food and lodging), which have not been valued by the community group and park authorities in the planning of conservation services and activities.
Poor access roads (unpaved roads), as well as the lack of parking for vehicles that causes damage to old buildings and the environment.
Selecting attributes and levels
From the diagnosis, working meetings with authorities of the CONANP (specialists in management of the PNA) and the research group were held with the purpose of determining the attributes or areas of intervention to evaluate, and their levels of intervention (from viable, realistic situations, and in the hopes of covering the possible preferences of the respondents). This implied the approach of improvements in the characteristics of the property in its current condition; that is, to move from the current situation to a situation with intervention. For example, the attribute “biodiversity protection“ in its current status (status quo) reveals fragmented habitat and wildlife hunting, due to little or no surveillance so it was placed in an ”insufficient" level. The first level of intervention, identified as the "good" level, consisted of increasing surveillance and reforesting with native species in order to mitigate habitat fragmentation; the second level, identified as the “excellent” level included species monitoring and implementation of livestock insurance for villagers in order to avoid hunting predators (felines). The remaining attributes and levels are presented in Table 1.
Attribute | Overview | Level |
---|---|---|
Biodiversity Protection | Fragmented habitat, little or no monitoring (current situation) | Insufficient (does not change) |
Reforestation with native species and increased surveillance | Good | |
Species monitoring and livestock insurance to mitigate predator hunting | Excellent | |
Creation and improvement of spaces for recreation | Lack of complementary services (current situation) | Insufficient (does not change) |
Food area with palapas, restaurant and children's playground | Good | |
Lodging cabins | Excellent | |
Forest health | Presence of pests and inappropriate care (current situation) | Insufficient (does not change) |
Pest monitoring and control in a timely manner | Good | |
Measures to control and restore affected areas | Excellent | |
Improved access roads and parking spaces | Unpaved road access, deteriorated main street and lack of parking places (current situation) | Insufficient (does not change) |
Exclusive site for parking on days of high tourist influx | Good | |
Improvement of site access roads | Excellent | |
Access fee (MXN) | There is currently no collection of fees for admission to the park | 10 |
15 | ||
20 | ||
25 |
To determine the levels of the price attribute, a pilot test was applied on the willingness to pay. This consisted of testing a questionnaire and openly asking interviewees for the rate they would be willing to pay for their entrance to the park after a situation of improvement in current conditions. The resulting levels were 10, 15, 20 and 25 MXN, values below the entry fee established (30.34 MXN) in the Federal Rights Act for 2016 (Congreso de la Unión, 2015).
According to the number of attributes and levels there are 324 possible combinations [(3 x 3 x 3 x 3) (4)], an unlikely situation to be performed, so we used fractional factor analysis through orthogonal design in the SPSS® statistical package (IBM SPSS Statistics, 2015) to minimize the correlation between attributes (Bennett & Adamowicz, 2001). Twenty five plans were generated that represent optimal, orthogonal and balanced scenarios (each level appears in the attribute the same number of times); however, one plan was inconsistent (the levels of the attributes are identical to the situation without intervention, but associated with a rate level) so it was discarded leaving only 24 plans.
Questionnaire design
A questionnaire with three sections was designed and developed. The first included general and environmental perception questions, and the second included questions related to the assessment of attributes of the site and the selection of the most preferred alternative, that is, the choice experiment (Table 2). Because it would be difficult for an interviewee to choose from 24 options, the questionnaire was divided into 12 versions. The third section investigated the socio-economic characteristics of the respondent, as well as suggestions for improving the tourism services of the site and the environmental management of the park. The interview explained each attribute and level in detail to the interviewees and showed representative images of the current situation and hypothetical scenarios of each of the proposed improvements.
Attribute | Alternative | ||
---|---|---|---|
A | B | Status quo | |
Protection of biodiversity | Good | Good | Does not change |
Creation and improvement of spaces for recreation Forest health | Does not change | Excellent | Does not change |
Improved access roads and parking spaces | Excellent | Good | Does not change |
Rate (MXN) | Good | Does not change | Does not change |
Choice | 10 | 25 | 0 |
Source: own production.
Sampling and obtaining of data
Sample size was estimated by simple random sampling using the population proportion methodology for finite populations. According to the logbook, in 2015, 5 240 visitors attended the PNLM, so a sample universe of 1 310 household heads was estimated, taking into account that the average family size in Mexico is four members (Consejo Nacional de Población [CONAPO], 2012). The information was collected in the sites of greater tourist inflow during the three high seasons of 2016 (easter, summer time and holiday), through 144 interviews with household heads, of whom only 141 were valid (on average 12 people responded to each of the 12 versions of the questionnaire).
Coding of the attributes to be valued
Prior to the estimation procedure, the attributes to be valued were coded to determine the effects in accordance with the process developed by Holmes and Adamowics (2003). Three levels were generated for each attribute: excellent, good and insufficient; the latter corresponds to the current situation, which means that the econometric analysis only works with excellent and good options (to avoid multicolinearity problems) (Greene, 2003). For the construction of the biodiversity protection (PB) attribute variables, when the interviewee chooses the "excellent" level, the value of 1 to EPB and 0 to BPB is assigned; if he chooses the “good” level, then the value of 1 to BPB and 0 to EPB is assigned, as shown in Table 3. The last situation is that the interviewee chooses the option "insufficient", in this case the variable is encoded with -1 (Holmes & Adamowics, 2003; Tudela, 2010; Tudela-Mamani & Leos-Rodriguez, 2018). All other attributes are encoded in the same way.
Chosen level | Protection of biodiversity | Spaces for recreation | Forest health | Access roads and parking | ||||
---|---|---|---|---|---|---|---|---|
EPB | BPB | EER | BER | ESF | BSF | EVA | BVA | |
Excellent | 1 | 0 | 1 | 0 | 1 | 0 | 1 | 0 |
Good | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 1 |
Insufficient | -1 | -1 | -1 | -1 | -1 | -1 | -1 | -1 |
EPB = excellent protection of biodiversity; BPB = good protection of biodiversity; EER = excellent space for recreation; BER = good space for recreation; ESF = excellent forest health; BSF = good forest health; EVA = excellent access routes; BVA = good access routes. Source: own elaboration based on the procedure developed by Holmes and Adamowics (2003) and Tudela-Mamani and Leos-Rodriguez (2018).
Results and discussion
The socio-economic profile of PNLM visitors indicates that the age of the heads of household varied between 30 and 49 years old (54 %); 75 % were male and 25 % female. Of the sample, 67 % have at least finished high school (just over 32 % with a bachelor's degree and 12 % with postgraduate studies). Most visitors (57 %) have incomes of less than 9 000 MXN per month and come mainly from two (Zimapán and Jacala) of the four municipalities where the park is located. Table 4 details the socio-economic characteristics of the visitors interviewed.
Variable | Category | Number | Percentage (%) |
---|---|---|---|
Sex | Woman | 38 | 27 |
Men | 103 | 73 | |
Age (years) | 18-29 | 32 | 23 |
30-39 | 34 | 24 | |
40-49 | 42 | 30 | |
50-59 | 24 | 17 | |
> 60 | 9 | 6 | |
Schooling | Truncated primary | 2 | 1 |
Full primary | 10 | 7 | |
Junior High school | 33 | 23 | |
High School | 32 | 23 | |
Bachelor | 45 | 32 | |
Post Graduate | 19 | 13 | |
Income (MXN) | ≤5 000 | 42 | 30 |
5 001 to 9 000 | 38 | 27 | |
9 001 to 17 000 | 39 | 28 | |
17 001 to 25 000 | 15 | 11 | |
> 25 000 | 7 | 5 | |
Willingness to pay (MXN) | 0 | 18 | 13 |
10.00 | 61 | 43 | |
15.00 | 21 | 15 | |
20.00 | 18 | 13 | |
25.00 | 23 | 16 |
Of the total number of interviewees, 13 % prefer that the current conditions of the site be maintained, which implied their willingness to pay equal to zero. On the other hand, three interviewees indicated that the implementation of the improvement program is the obligation of the authorities, so they were considered protest responses and were not included in the Econometric Analysis.
Econometric analysis of attribute valuation
From the coded data, the econometric analysis was done to estimate the parameters with the maximum likelihood estimation procedure (Greene, 2003), through an LMN (Riera & Mogas, 2006; Tudela, 2010) with the R® statistical software (R Core Team, 2016) and the support packages.CEs (Aizaki, 2012) and survival (Therneau, 2015). Two models were generated; the first considered the cross-effects between the socio-economic characteristics of the users and the constants specific to each alternative of choice (model with interactions). Both the income level and education showed a direct and significant relationship; however, in the face of possible problems of sample correlation, the additive model or without interactions was chosen, which presented a better fit.
Table 5 shows the main results of the full and reduced econometric models. For the latter, only the variables with a significance level greater than 90 % (P ≤ 0.1) were chosen, which showed a positive sign for the attributes-levels and a negative sign for the entry rate. In the reduced model, the most significant variables were BPB, ESF, EVA, Entry Rate (P ≤ 0.01) and BSF (P ≤ 0.05). None of the variables related to the attribute creation and improvement of spaces for recreation (EER and BER) were statistically significant. It is considered that there was a good fit in terms of pseudo-R2 adjusted (0.25), since it is within the recommended range for this type of study (0.20 to 0.40) and which is equivalent to an R2 of 0.70 to 0.90 for the case of the regression by ordinary least squares (Alvarez-Farizo et al., 2006; Tudela, 2010). For its part, the Chi-square test rejects the hypothesis that the slopes of the model are equal to zero (P ≤ 0.01).
Variable | Full model | Reduced model |
---|---|---|
ASC | 0.010 (0.830) | ns |
Rate | -0.066 * * (0.030) | -0.054 * * * (0.017) |
EPB | -0.295 (0.352) | ns |
BPB | 0.560 * * (0.223) | 0.503 * * * (0.146) |
EER | -0.171 (0.398) | ns |
BER | 0.409 (0.256) | ns |
ESF | 0.500 * *(0.239) | 0.540 * * * (0.205) |
BSF | 0.460 * * (0.193) | 0.354 * * (0.161) |
EVE | 0.573 *(0.314) | 0.745 * * * (0.178) |
BVA | 0.173 (0.306) | ns |
Comment | 423 | 423 |
Probability Log | -108.032 | -111.053 |
LR test | 93.745*** | 87.703*** |
McFadden R2 | 0.302 | 0.283 |
McFadden R2 adjusted | 0.238 | 0.250 |
Akaike information criterion | 236.063 | 232.105 |
ASC = specific alternative constant (intercept); EPB = excellent protection of biodiversity; BPB = good protection of biodiversity; EER = excellent space for recreation; BER = good space for recreation; ESF = excellent forest health; BSF = good forest health; EVA = excellent access routes; BVA = good access routes; LR = probability ratio. Significance level: ** P ≤ 0.05; *** P ≤ 0.01; not significant (ns). Coefficients standard errors are in parentheses.
The additive model indicates that the level of utility that interviewees perceive increases if the proposed improvements are applied in the areas of intervention; that is, they value improvements in forest health, access routes and protection of biodiversity and exclude improvement in recreation spaces. On the other hand, it is confirmed that the level of utility of the respondents decreases with higher rates of entry to the PNLM, which is consistent with economic theory.
At the same time, the Hausman and McFadden test (Greene, 2003) produced the following results: Plan A = 6.3557, Plan B = 9.2799 and status quo = 2.3938. In all three cases, the statistic was less than the critical Chi-Square value (P ≤ 0.05; gl = 5, X2 = 11.0705), which demonstrated that there was insufficient statistical evidence to reject the IIA restriction and that the LMN model is appropriate.
Analysis of marginal willingness to pay
The coefficients obtained from the parameters of the additive conditional logit model were replaced in the DAPMg formula for each attribute. The results show that interviewees assigned higher DAPMg to improvements in access roads and parking sites on a good level (13.74 MXN). This data differs from that reported by Tudela (2010), who found that visitors to the Molino de Flores National Park in the State of Mexico value this attribute less; however, the result is consistent with the answers to the direct question that was asked to visitors about priorities to create better conditions in tourism activity, and with what was found in participatory diagnostic workshops. This reflects a widespread real need, taking into account that the conditions of access to the site are by dirt track on a path of approximately 6 km.
Although the biodiversity protection attribute is important, as it generates stability in the ecosystem and allows users to have scenic beauty, the interviewees showed a higher level of preference towards other attributes. It is natural that these preferences are due to safety and comfort interests in a timely and immediate manner; however, visitors feel the need to preserve the environment that will subsequently contribute to the expected Community Economic Development.
Second in importance, respondents ranked forest health intervention at an excellent level (9.97 MXN) and another smaller group considered paying only 6.54 MXN (good level). It is likely that the respondents prioritize the improvement in the attribute of forest health in the two levels of intervention, due to the increasing presence of affectations plant-associated pest bark beetle in the PNLM (CONAFOR, 2015; Del-Val & Sáenz-Romero, 2017) and technical reports, sanitation forestry in the PNLM, provided by operational staff of CONANP). The population knows this situation at the regional level and may have influenced the choice of improvement plans, considering that 51 % of the interviewees are from municipalities that make up the PNLM.
Attribute | DAPMg (MXN) | Lower limit (5 %) | Upper limit (95 %) |
---|---|---|---|
Good protection of biodiversity | 9.28 | 5.11 | 18.06 |
Good forest health | 6.54 | 1.90 | 14.02 |
Excellent forest health | 9.97 | 3.61 | 22.67 |
Excellent improvement of access roads and parking places | 13.74 | 7.80 | 27.55 |
On the other hand, the attribute improvement in spaces for recreation was not significant (P > 0.05). This result coincides with what Tudela (2010) reports in his research on choice experiments in the prioritization of management policies in the Molino de Flores National Park, where visitors expressed a greater preference for the improvement of plant cover and for the restoration of old buildings. In forest ecosystems on Navarino Island in Chile, Cerda (2010) evaluated the economic preferences of the local community to development options that involved some loss of Environmental Services and found that a low-impact development model represented by low-scale tourism was favoured. In both cases and in the present study congruence is observed in preferences for attributes involving environmental improvements. On the contrary, given the increase in the area of forests in Catalonia, Riera and Mogas (2006) found that the attribute of greatest value for users was the collection of mushrooms and field days, while the least valued corresponded to erosion control.
From these results, the responsible of the administration of the PNLM have more information for designing the strategies of management of environmental assets; for example, in the planning of ecotourism activities the improvements in the attributes with higher implicit prices should be prioritized (forest health and biodiversity protection and access roads) and secondly the less valued by the interviewees (creation and improvement of the spaces for the recreation). This indicates that the respondents assess the current pristine conditions of the site where the conservation of the environment is favored, which guides to make minimal changes to the tourist infrastructure; in this sense, improvements should be focused only on compliance with the applicable rules on eco-tourism and adventure tourism.
This argument reinforces the points made by Martínez (2015) and Mendoza, Figueroa, and Godinez (2015), who indicate that the management policies of the NPA must be approached with a vision that includes all the actors involved (users and residents of the communities within the PNLM and its area of influence) in these areas of Environmental Conservation and that they seek Development Alternatives in communitarian tourism (López, Favila, Hernández, Guzmán, & Osorio, 2019). In this sense, the choice experiments are a useful tool to replicate in order to help the management of handling policies in National Parks, areas of protection of Flora and Fauna, and Biosphere Reserves, considering that at least 100 of the federal NPAs have the tourist potential for their visitation (CONANP, 2019).
Conclusions
Visitors to Los Mármoles National Park are willing to pay more for improved forest health and biodiversity protection in an aggregate manner (16.51 MXN), followed by improvements in access roads and parking spaces (13.74 MXN). The conditioning of spaces for recreation was not significant, reflecting the social preference for the conservation of undisturbed landscape conditions. The use of choice experiments in the management of policies for the handling of protected natural areas allowed the identification of areas of opportunity with the opinion of the actors involved in the planning of the daily activities, exploitation and conservation in these protected areas. Those responsible for the administration of protected natural areas should assess the evidence obtained in the formulation of management plans that generate greater social benefit, ecosystem conservation and mitigation of the effects of climate change.